Examining the Relationship Between Financial Statement Fraud Detection Models and Auditor Skepticism Levels

Posted: Feb 04, 2025

• Luna Flores
• Luna Garcia
• Luna Jones

Abstract

This research investigates the complex interplay between advanced financial statement fraud detection models and auditor professional skepticism levels, presenting a novel framework that challenges conventional approaches to fraud detection in accounting practice. Traditional fraud detection methodologies have primarily focused on either technological solutions or human judgment factors in isolation, creating a significant gap in understanding how these elements interact dynamically. Our study introduces an innovative hybrid methodology that combines machine learning algorithms with psychological assessment tools to measure and analyze the bidirectional relationship between technological fraud detection capabilities and auditor skepticism. We developed and tested a comprehensive model involving 157 practicing auditors from diverse accounting firms, employing both quantitative analysis of fraud detection accuracy and qualitative assessment of skepticism development through controlled experimental scenarios. The findings reveal a previously undocumented paradoxical relationship: while sophisticated fraud detection models initially enhance auditor skepticism through improved fraud identification, prolonged reliance on these systems can lead to skepticism attenuation through automation complacency effects. Furthermore, we identified specific threshold points where technological assistance transitions from skepticism enhancement to dependency creation, providing crucial insights for optimal system design and implementation. This research contributes original theoretical frameworks for understanding human-technology interaction in professional judgment contexts and offers practical guidance for developing balanced fraud detection ecosystems that leverage technological advantages while preserving essential human cognitive functions in auditing practice.